We then adopt the margin ranking loss [1]}, [2]} to construct the Gnoise metric space and Gblur metric space.
The margin ranking loss is defined as:
\(\mathcal {L}_{ML} &= \frac{1}{2N}\sum _{i,j}^{N}\mathtt {max}(0,\gamma -\delta (\mathbf {s}_i, \mathbf {s}_j)\cdot (\hat{\mathbf {s}}_i - \hat{\mathbf {s}}_j)) \\\delta (\mathbf {s}_i, \mathbf {s}_j) &= \left\lbrace \begin{aligned}1,\ \mathbf {s}_i \ge \mathbf {s}_j\\-1,\ \mathbf {s}_i < \mathbf {s}_j,\end{aligned}\right.\) 
